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We’re Drowning in Data—But Starving for Insight

Michael Lee, MBA
Aug 1
3 min read

If you’ve ever looked at a beautifully formatted dashboard and still found yourself asking, "So... what does this actually tell me? "You’re not alone.

In today’s business world, we have no shortage of data. Sales reports, customer surveys, finance trackers, performance dashboards—they’re everywhere. But ironically, more data hasn’t made decisions easier.

Instead, we find ourselves buried in reports, unable to spot what really matters:

Which product lines are quietly losing traction?
Where are our customers dropping off—and why?
Why did that campaign succeed in one region but flop in another?

Despite having data, we often rely on instinct. Or worse—assumptions. The problem isn’t the numbers. The problem is that we’re not trained to explore them meaningfully.

The Gap Between Reports and Real Answers

Let’s be honest—most people aren’t taught how to think with data.

They know how to build charts. They know how to create pivot tables.But when asked "What’s really going on here?", things fall apart.

Why?

Because we’ve been taught to summarize data, not explore it.We’ve been shown how to “clean” data, but not how to “mine” it for insight.

Here’s the distinction:

Reporting answers “what happened?”
Data mining starts asking “why did it happen?” and “what else is changing?”

That shift—from reporting to exploring—is what separates great analysts and decision-makers from the rest.

Business Example: The Case of the Disappearing Customers

Imagine you're an e-commerce manager.Sales dropped last quarter, but nothing on your dashboard stands out. Conversion rates? Normal. Traffic? Stable. Product reviews? Decent.

You decide to do a deeper dive using past order history and filtering by first-time buyers. Suddenly, a pattern emerges: a sharp decline in repeat purchases from customers who bought via a specific payment channel. That’s not something your usual dashboard would show. But a bit of structured data exploration—mining for trends over time—brings it to light.

You didn’t need a PhD or Python script. You just needed the right questions and an analytical process.

Public Sector Example: Reading Between the Reports

Let’s take another scenario, this time from the public service.

A government team rolls out a grant for community initiatives. Reports show that applications have slowed. Everything seems business-as-usual—budget reports, geographic breakdowns, prior-year comparisons.

But one officer notices that applications dipped sharply in a specific district. She examines the data month-by-month and finds that the downturn started just after several community centres in that area closed for renovation. Access, not interest, was the issue.

That simple time-based exploration—often overlooked—unlocked a critical insight. Without it, they might’ve incorrectly assumed the grant was no longer effective.

This is the power of trend-based mining. It doesn't require technical complexity. It just requires knowing how to look.

But I’m Not a Data Analyst...

Exactly. That’s who this course is for.

At FYT, we designed FYTBA02: Data Mining and Analysis for working professionals—not data scientists.

If you're in sales, HR, marketing, operations, finance, or public service—this class helps you move from simply reporting data to understanding what it’s trying to tell you.

Whether you're: